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- W2752358423 abstract "We describe our system for participating in SemEval-2017 Task 3 on Community Question Answering. Our approach relies on combining a rich set of various types of features: semantic and metadata. The most important group turned out to be the metadata feature and the semantic vectors trained on QatarLiving data. In the main Subtask C, our primary submission was ranked fourth, with a MAP of 13.48 and accuracy of 97.08. In Subtask A, our primary submission get into the top 50%." @default.
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- W2752358423 date "2017-01-01" @default.
- W2752358423 modified "2023-10-17" @default.
- W2752358423 title "EICA Team at SemEval-2017 Task 3: Semantic and Metadata-based Features for Community Question Answering" @default.
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- W2752358423 doi "https://doi.org/10.18653/v1/s17-2047" @default.
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